Sunday, August 7, 2016

Estimating the Causal Effect of Advising Contacts on Fall to Spring Retention Using Propensity Score Matching and Inverse Probability of Treatment Weighted Regression

Matt Bogard, Western Kentucky University

Abstract

In the fall of 2011 academic advising and residence life staff working for a southeastern university utilized a newly implemented advising software system to identify students based on attrition risk. Advising contacts, appointments, and support services were prioritized based on this new system and information regarding the characteristics of these interactions was captured in an automated format. It was the goal of this study to investigate the impact of this advising initiative on fall to spring retention rates. It is a challenge on college campuses to evaluate interventions that are often independent and decentralized across many university offices and organizations. In this study propensity score methods were utilized to address issues related to selection bias. The findings indicate that advising contacts associated with the utilization of the new software had statistically significant impacts on fall to spring retention for first year students on the order of a 3.26 point improvement over comparable students that were not contacted.

Suggested Citation

Matt Bogard. 2013. "Estimating the Causal Effect of Advising Contacts on Fall to Spring Retention Using Propensity Score Matching and Inverse Probability of Treatment Weighted Regression" The SelectedWorks of Matt Bogard
Available at: http://works.bepress.com/matt_bogard/25

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